Speeded Up Robust Features

	Speeded Up Robust Features In computer vision, speeded up robust features (SURF) is a patented local feature detector and descriptor. It can be used for tasks such as object recognition, image registration, classification, or 3D reconstruction. It is partly inspired by the scale-invariant feature transform (SIFT) descriptor. The standard version of SURF is several times faster than SIFT and claimed by its authors to be more robust against different image transformations than SIFT. To detect interest points, SURF uses an integer approximation of the determinant of Hessian blob detector, which can be computed with 3 integer operations using a precomputed integral image. Its feature descriptor is based on the sum of the Haar wavelet response around the point of interest. These can also be computed with the aid of the integral image. SURF descriptors have been used to locate and recognize objects, people or faces, to reconstruct 3D scenes, to track objects and to extract points of interest. SURF was firs ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
picture info	Computer Vision Computer vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to understand and automate tasks that the human visual system can do. Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g. in the forms of decisions. Understanding in this context means the transformation of visual images (the input of the retina) into descriptions of the world that make sense to thought processes and can elicit appropriate action. This image understanding can be seen as the disentangling of symbolic information from image data using models constructed with the aid of geometry, physics, statistics, and learning theory. The scientific discipline of computer vision is concerned with the theory ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
picture info	Gaussian Smoothing In image processing, a Gaussian blur (also known as Gaussian smoothing) is the result of blurring an image by a Gaussian function (named after mathematician and scientist Carl Friedrich Gauss). It is a widely used effect in graphics software, typically to reduce image noise and reduce detail. The visual effect of this blurring technique is a smooth blur resembling that of viewing the image through a translucent screen, distinctly different from the bokeh effect produced by an out-of-focus lens or the shadow of an object under usual illumination. Gaussian smoothing is also used as a pre-processing stage in computer vision algorithms in order to enhance image structures at different scales—see scale space representation and scale space implementation. Mathematics Mathematically, applying a Gaussian blur to an image is the same as convolving the image with a Gaussian function. This is also known as a two-dimensional Weierstrass transform. By contrast, convolving by a circle ( ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Blob Detection In computer vision, blob detection methods are aimed at detecting regions in a digital image that differ in properties, such as brightness or color, compared to surrounding regions. Informally, a blob is a region of an image in which some properties are constant or approximately constant; all the points in a blob can be considered in some sense to be similar to each other. The most common method for blob detection is convolution. Given some property of interest expressed as a function of position on the image, there are two main classes of blob detectors: (i) '' differential methods'', which are based on derivatives of the function with respect to position, and (ii) ''methods based on local extrema'', which are based on finding the local maxima and minima of the function. With the more recent terminology used in the field, these detectors can also be referred to as ''interest point operators'', or alternatively interest region operators (see also interest point detectio ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	LESH Lesh is both a surname and a given name. Notable people with the name include: Surname: * Fyodor Lesh (1840 - 1903), physician * Pavel Lesh (1887 - 1915), sport shooter * Phil Lesh (born 1940), musician * Richard Lesh, professor * Ulysses Samuel Lesh (1868-1965), politician Given name: * Lesh Shkreli (born 1957), footballer See also * Lesch, a surname * Loesch * Losch * LESH * Phil Lesh and Friends * Lezhë Lezhë (, sq-definite, Lezha) is a city in the Republic of Albania and seat of Lezhë County and Lezhë Municipality. One of the main strongholds of the Labeatai, the earliest of the fortification walls of Lezhë are of typical Illyrian const ... {{given name, type=both Albanian masculine given names ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	GLOH GLOH (Gradient Location and Orientation Histogram) is a robust image descriptor that can be used in computer vision tasks. It is a SIFT-like descriptor that considers more spatial regions for the histograms. An intermediate vector is computed from 17 location and 16 orientation bins, for a total of 272-dimensions. Principal components analysis (PCA) is then used to reduce the vector size to 128 (same size as SIFT descriptor vector). See also * Scale-invariant feature transform * Speeded Up Robust Features * LESH – Local Energy-based Shape Histogram * Feature detection (computer vision) In computer vision and image processing, a feature is a piece of information about the content of an image; typically about whether a certain region of the image has certain properties. Features may be specific structures in the image such as poi ... References Krystian Mikolajczyk and Cordelia Schmid "A performance evaluation of local descriptors", IEEE Transactions on Pattern Analysis ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]